yzou2 Goto Github PK
Name: Yang Zou
Type: User
Company: Amazon Web Services
Bio: Sr. Applied Scientist at AWS AI Labs. PhD @ Carnegie Mellon University.
Blog: https://yzou2.github.io/
Name: Yang Zou
Type: User
Company: Amazon Web Services
Bio: Sr. Applied Scientist at AWS AI Labs. PhD @ Carnegie Mellon University.
Blog: https://yzou2.github.io/
Easily create a beautiful website using Academic and Hugo
Samples for the Anomaly Detection API documentation:
:city_sunrise: A collection of links for free stock photography, video and Illustration websites
Code for <Domain Adaptation for Semantic Segmentation via Class-Balanced Self-Training> in ECCV18
Framework for optimizing CNNs with linear constraints.
CMU-16720 Computer Vision Course Homeworks
Code for <Confidence Regularized Self-Training> in ICCV19 (Oral)
Data Lake as Code, featuring ChEMBL and OpenTargets
Deep Residual Learning for Image Recognition
A higher performance pytorch implementation of DeepLab V3 Plus(DeepLab v3+)
深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述,以帮助自己及有需要的读者。 全书分为18个章节,50余万字。由于水平有限,书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作,联系[email protected] 版权所有,违权必究 Tan 2018.06
A PyTorch Implementation for Densely Connected Convolutional Networks (DenseNets)
Depth-aware CNN for RGB-D Segmentation, ECCV 2018
CVPR2019 Joint Discriminative and Generative Learning for Person Re-identification
Joint Disentangling and Adaptation for Cross-Domain Person Re-Identification. ECCV'20 (Oral)
Pytorch Implementation -- All about Structure: Adapting Structural Information across Domains for Boosting Semantic Segmentation, CVPR 2019
Domain Adaptation Representation Learning Algorithm (as published in JMLR 2016)
PyTorch implementation of Deep Ordinal Regression Network for Monocular Depth Estimation
An Personal Note for DS/ML interview questions
starter from "How to Train a GAN?" at NIPS2016
A free and unlimited API for Google Translate :dollar::no_entry_sign:
Unsupervised Feature Learning via Non-parametric Instance Discrimination
Machine learning interview questions and answers
This repository is to prepare for Machine Learning interviews.
Preparing for machine learning interviews
A multi-task learning example for the paper https://arxiv.org/abs/1705.07115
This is a multilabel classification layer for mxnet.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.